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FastPart — camera-ready best partitions (Titan23, ε = 2 %, K = 2/3/4)

This repository holds the partitions produced by an improved to-be-released FastPart solver (developed under the internal codename CORD) on the 22 Titan23 designs at ε = 2 % for K = 2, 3 and 4 — 66 cells in total. Benchmarks are not redistributed here; only the resulting assignments. For the actual FastPart solver which appeared at ICCAD 2026, see the src branch called iccad26-camera-ready in this same repo (that branch should replicate results in the paper, while the cuts in the main branch are better than what the paper reports).

CORD is under active development and iteration, and will be hopefully released soon.

Every cut in the table below was re-scored, immediately before publication, by the independent golden evaluator directly from the .part file shipped in best-partitions/ — 66 of 66 verified, zero mismatches. The fourth column is the target these runs were chasing: min(KEP, FastPart-original), the best value previously attained by either the KEP solver or the original FastPart.

Result

WIN (below target) TIE (equal) above target geomean cut / target
All 66 cells 30 35 1 0.9941
K = 2 3 19 0 0.9994
K = 3 12 10 0 0.9925
K = 4 15 6 1 0.9905

65 of 66 cells meet or beat the target; the geometric mean cut is 0.59 % below it. The single exception is gsm_switch K = 4.

Balance convention

Two-sided, absolute. For a hypergraph of total vertex weight W, every block b satisfies

ceil((1/K − ε/100)·W)  ≤  w_b  ≤  floor((1/K + ε/100)·W)

so at K = 4, ε = 2 % each block holds between 23 % and 27 % of the weight. The objective is cut-net (each hyperedge spanning more than one block counts once, times its weight). Every partition below is legal under this convention.

Files

best-partitions/<instance>.k<K>.part.gz — gzip of a plain text file with one block index per line, in vertex order, 0-based, n lines for n vertices.

gunzip -c best-partitions/directrf.k2.part.gz | head

Results table

Cut = the value achieved by these partitions. Target = min(KEP, FastPart-original).

Instance K Cut (FastPart camera-ready) Target = min(KEP, FastPart-original)
LU230 2 3265 3277
LU230 3 4391 4484
LU230 4 5315 5444
LU_Network 2 524 524
LU_Network 3 784 784
LU_Network 4 1351 1352
SLAM_spheric 2 1061 1061
SLAM_spheric 3 2644 2684
SLAM_spheric 4 3117 3137
bitcoin_miner 2 1489 1489
bitcoin_miner 3 1806 1831
bitcoin_miner 4 1830 1831
bitonic_mesh 2 581 581
bitonic_mesh 3 889 895
bitonic_mesh 4 1085 1087
cholesky_bdti 2 1156 1156
cholesky_bdti 3 1647 1665
cholesky_bdti 4 1844 1844
cholesky_mc 2 282 282
cholesky_mc 3 787 787
cholesky_mc 4 975 975
dart 2 784 784
dart 3 1070 1083
dart 4 1244 1279
denoise 2 416 416
denoise 3 715 720
denoise 4 843 847
des90 2 371 371
des90 3 504 504
des90 4 654 656
directrf 2 490 490
directrf 3 711 711
directrf 4 1027 1030
gsm_switch 2 1479 1479
gsm_switch 3 2324 2345
gsm_switch 4 2781 2751
mes_noc 2 633 633
mes_noc 3 1094 1105
mes_noc 4 1306 1306
minres 2 207 207
minres 3 309 309
minres 4 405 405
neuron 2 243 243
neuron 3 362 362
neuron 4 405 405
openCV 2 428 432
openCV 3 492 492
openCV 4 508 515
segmentation 2 107 107
segmentation 3 447 447
segmentation 4 479 479
sparcT1_chip2 2 873 874
sparcT1_chip2 3 1256 1297
sparcT1_chip2 4 1480 1531
sparcT1_core 2 974 974
sparcT1_core 3 1717 1762
sparcT1_core 4 2162 2174
sparcT2_core 2 1183 1183
sparcT2_core 3 2053 2059
sparcT2_core 4 2777 2851
stap_qrd 2 370 370
stap_qrd 3 462 462
stap_qrd 4 633 675
stereo_vision 2 169 169
stereo_vision 3 320 320
stereo_vision 4 370 372

Verification

Score any file against its benchmark with the cut-net objective and check the two-sided window above. SHA-256 of each uncompressed .part payload:

File SHA-256 (uncompressed)
LU230.k2.part.gz ceb9f66f8ba5a47dd64d995a49d246f50e40fc40750757bdebb412ea5e6778de
LU230.k3.part.gz 3409eeec7fd1af109d9106bc3bd4a4e401ed1afbd421a8191c9b9c5523f14902
LU230.k4.part.gz 599c03580a94636972cf4fa3b43f21de25baf9164ce3a39745b8cc42e38a5820
LU_Network.k2.part.gz 961d5aba067390eeb5692290a57bf08d83832b6a879f425a189f30e8a895071c
LU_Network.k3.part.gz b96074bd5c8b282e298e2989a85d39a91367702eb090255c4d184a721bf18b7e
LU_Network.k4.part.gz ba3cbce3b288f2964d861804c3df3d1b384d2c130b2438864d414ce328e1a947
SLAM_spheric.k2.part.gz 0843585c00d2484a4f7d2974113940bcd0603c49cf2137c187cdd1ffd46e2450
SLAM_spheric.k3.part.gz fedf6d720933cf647b0823b6bf14fafd21db2c534b65abe6aaf65aef1d2c9844
SLAM_spheric.k4.part.gz da96e8152b9ebb4eb21d5af61deffed2ea995c676cb0a06e034688dea9d2e4b3
bitcoin_miner.k2.part.gz 1b8027ccc0ca7b19456a1198c8c3fe7c24729001f1d6c5191e8d186193d06cdd
bitcoin_miner.k3.part.gz c57514add8484ea13314de7072773481ecb22198811519fa18fb290759b54438
bitcoin_miner.k4.part.gz f1e33c73d3d38deef6f633a0eeca1b2d9982d8bafab2d9387badc841fafe179d
bitonic_mesh.k2.part.gz 55e9a467087a237a95868d7ef98eb105ed4da4bb3f4f6506a099ceb835c26b87
bitonic_mesh.k3.part.gz f673e602b512f2baccacd6f06312d8f48e521b06c54b02ab28d2cc059c0ce7d0
bitonic_mesh.k4.part.gz f7cc497b7e7010303ba26d20ddcb46bdabac3c22d676468a77e1516e56774758
cholesky_bdti.k2.part.gz d669c8d52473025dc96ac5b8b4f3e6222851d0c314b8c0143ff811ecb351fe46
cholesky_bdti.k3.part.gz 8c2f508c0f7a8180514c1bf7efb63e88de023e5fe10f57a8a0ef413555af65d7
cholesky_bdti.k4.part.gz b0ddd1a590b334f5605e903b6dad6f3be2aed88d4314d3e9d931f8e3f18cfbea
cholesky_mc.k2.part.gz 265d42f3a4d63c534a6ff18b572c44e48320727332d17ac154c65d7974139261
cholesky_mc.k3.part.gz 1aa39ef91961365dae253b34017e69598002a628219eac7220bd034005426b05
cholesky_mc.k4.part.gz c55ddb1b77affe8bde9864bde9b0d7879276c8faf954b693ce8c85e6e954a9e0
dart.k2.part.gz da7c4ec36b8a8798e432ffeecdef6160c44b4efdaded1507c93eae1ac2c56731
dart.k3.part.gz 51fd75127b44dffed27ac4bcbba199ad53cef6120a2e28d21cc3a6fa519f87fc
dart.k4.part.gz c8c26c498a8a21b5d30fc1166237546ac717887741bd3c1d8db94a1dc0400329
denoise.k2.part.gz 8150e37951f578463d5940f1166c806962235249b4933c76b01f97905723b400
denoise.k3.part.gz 86d1b9c9acda4d9f5b3a4931acbfc14bf571340330f29305a83e2a2b313e0397
denoise.k4.part.gz 6fc33e07947779dfc384e0e5c4b633217126b74ad3e162fc052e1875bb4f27b7
des90.k2.part.gz d080944518c2d65acc1da9baa2e29567085b0db308bf703d2c83ba9e3746a71e
des90.k3.part.gz d01bb8badd34fb5bcbdfc5586d1c0aac722226c62cde6b6f62b241f318bcf586
des90.k4.part.gz 83cbcb5c5740386cfb5c94e7207c29b0b3fc14244b2147fd971b3d4657a41177
directrf.k2.part.gz 7cc6a7e0f43ac413c6535f23a5dd5d655fcdd510223a07f464575b27887b6f1f
directrf.k3.part.gz 2f49842efbb3ba46d8ced6534adece9a0fac4351d091cf69052ab66334b34981
directrf.k4.part.gz b80234bd75298df04efb07f1b63df0301dd649ab1337f0611eb10172bf241793
gsm_switch.k2.part.gz 56d5ef210e4641e639df6441bd566769a91f858a09d897b5214ab73ba5fb588a
gsm_switch.k3.part.gz b14e9d2ac4258762b68690f6b9e78d64e6af2fe7df252ea19fd12b382b887d8d
gsm_switch.k4.part.gz 01f334a4962acce8f3931c3b4546973ae6212bb9714d9280e55869bbea1fe82d
mes_noc.k2.part.gz 5a7ae0c6bb7009a7be227d183171d06d5371e8ab1e11d2350186b7b3f179e2e2
mes_noc.k3.part.gz f811808b2c4cd8667cfef2e0bd4ccad16c282210c503c9d73cb317edaf0f9a4c
mes_noc.k4.part.gz ed21d4bc612b617521308757c75c519ded422a169d14777730308c0f0ecef5cf
minres.k2.part.gz c80d8b8a56b44765e91b580e532c792d97781c3f5e347b6645538c0742611ab0
minres.k3.part.gz 115fd615d4677936ce146b69cac83e9bb7972763c669af64a010f14b5bf470fb
minres.k4.part.gz 336d7b3ac300926774ee7190993deb467ee0de6d8002ee96dd45c53e54342ec1
neuron.k2.part.gz 4ad73ece425d802638daf2a36ce83b66a9df7b04efa620d88f1201196a3c54c5
neuron.k3.part.gz 2cbb19f47c49f44d31c2397c8749abf8eadddefe24bc24139f5b7e7e6d39a38a
neuron.k4.part.gz 44ca286e8de7a835e1fd772ee886cf89765c7df9d1ccb68b05d21d6dd8874e96
openCV.k2.part.gz d62d0604efd86cdb5205dbc095a2f7f92b93cdd438352683fde964d18bb1d823
openCV.k3.part.gz c8a255cf0a918a15ae24fddc7454604c4d7abc6e7502f2955801f3b6fcbd0770
openCV.k4.part.gz 844f63abfbeaca1d0eadf957f988263b923eaeed91265abe0f16704624de8d85
segmentation.k2.part.gz 54d3356c14422b628e6ecc26cb2d45a9fb5c4cf30a32c5431d84a318830f33fd
segmentation.k3.part.gz 238bf5bedce58c2c2fddbeeba0eaa3981a607f31492e81eae39609f04404dcc2
segmentation.k4.part.gz 91a4ae02ee8ea26f4268ca09dee1bfbbf431b05f2cc1b3cce036b7202dfa0481
sparcT1_chip2.k2.part.gz 7f4afeb0f4041a3ce200cf1fa6ae0a5bb15d8a61660e4a8000656641dd0737dd
sparcT1_chip2.k3.part.gz 053ad6e50101511fafe95a7ea451498c1f7c87a56963a21c494f191b9afbfe8b
sparcT1_chip2.k4.part.gz 2aad8641682239922cf4bc3a54cb27a3e0fc85f1464d05f02b358085e09be0f5
sparcT1_core.k2.part.gz bb8e101577801a744bfb26974a9f65c056cd33986c99717eb9bba5a11f6744bd
sparcT1_core.k3.part.gz 7f1817c3f0e8f593aa88a5574eb16b9e64637d925a24736834c0d108f11a5054
sparcT1_core.k4.part.gz 8c2cabdcbacf3f44cc347fc70f845f196aa224454c2bbadad1c75c668d8e5035
sparcT2_core.k2.part.gz 29f5ce5958a0694784739409991c12ebd12f21d3c2e9eb60ff19eba29eff8ced
sparcT2_core.k3.part.gz e5fbabbea738d9eb66887fea09c6377b67f46ea80a894143d75849639ec54cd3
sparcT2_core.k4.part.gz 88bd0b47b85e2afd522c0a1f24d0c5bf8319923c540e2e0129c37cfe0a7c4326
stap_qrd.k2.part.gz 29ba0008c95d1135ecc051b5d1473b68b192572eddc5bdd109a09f2c85ff25be
stap_qrd.k3.part.gz 7b4eda8d78a1ebc511379cb6df038a570d1472c597cb183010dff9b3c051e4e7
stap_qrd.k4.part.gz 80f3bc5a07db6483f6196f53d1d020bc3325ff99faf0442a3f43159d60356818
stereo_vision.k2.part.gz a08baf4b42855d18a3550848bbde702960b0b3aa65feb9dd93308f672573aed0
stereo_vision.k3.part.gz 0761d799942f6094babff61f9301061b6cbc5747bc50100ddc5586c43a4ba4ee
stereo_vision.k4.part.gz 8a876700d06b9a1111a0233879b00d218258383cfef286b5015a25a9aa026d93

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ICCAD 2026 FastPart artifacts

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